Mechanistic study and precision treatment of primary liver cancer (PLC) are hindered by marked heterogeneity, which is challenging to recapitulate in any given liver cancer mouse model. Here, we report the generation of 25 mouse models of PLC by in situ genome editing of hepatocytes recapitulating 25 single or combinations of human cancer driver genes. These mouse tumors represent major histopathological types of human PLCs and could be divided into three human-matched molecular subtypes based on transcriptomic and proteomic profiles. Phenotypical characterization identified subtype- or genotype-specific alterations in immune microenvironment, metabolic reprogramming, cell proliferation, and expression of drug targets. Furthermore, single-cell analysis and expression tracing revealed spatial and temporal dynamics in expression of pyruvate kinase M2 ( Pkm2 ). Tumor-specific knockdown of Pkm2 by multiplexed genome editing reversed the Warburg effect and suppressed tumorigenesis in a genotype-specific manner. Our study provides mouse PLC models with defined genetic drivers and characterized phenotypical heterogeneity suitable for mechanistic investigation and preclinical testing.
Background Molecular features underlining the multistage progression of gastric lesions and development of early gastric cancer (GC) are poorly understood, restricting the ability to GC prevention and management. Methods We portrayed proteomic landscape and explored proteomic signatures associated with progression of gastric lesions and risk of early GC. Tissue proteomic profiling was conducted for a total of 324 subjects. A case-control study was performed in the discovery stage (n=169) based on populations from Linqu, a known high-risk area for GC in China. We then conducted two-stage validation, including a cohort study from Linqu ( n = 56), with prospective follow-up for progression of gastric lesions (280–473 days), and an independent case-control study from Beijing ( n = 99). Findings There was a clear distinction in proteomic features for precancerous gastric lesions and GC. We derived four molecular subtypes of gastric lesions and identified subtype-S4 with the highest progression risk. We found 104 positively-associated and 113 inversely-associated proteins for early GC, with APOA1BP, PGC, HPX and DDT associated with the risk of gastric lesion progression. Integrating these proteomic signatures, the ability to predict progression of gastric lesions was significantly strengthened (areas-under-the-curve=0.88 (95%CI: 0.78–0.99) vs. 0.56 (0.36–0.76), Delong's P = 0.002). Immunohistochemistry assays and examination at mRNA level validated the findings for four proteins. Interpretation We defined proteomic signatures for progression of gastric lesions and risk of early GC, which may have translational significance for identifying particularly high-risk population and detecting GC at an early stage, improving potential for targeted GC prevention. Funding The funders are listed in the Acknowledgement.
Signaling pathway alterations in COVID-19 of living humans as well as therapeutic targets of the host proteins are not clear. We analyzed 317 urine proteomes, including 86 COVID-19, 55 pneumonia and 176 healthy controls, and identified specific RNA virus detector protein DDX58/RIG-I only in COVID-19 samples. Comparison of the COVID-19 urinary proteomes with controls revealed major pathway alterations in immunity, metabolism and protein localization. Biomarkers that may stratify severe symptoms from moderate ones suggested that macrophage induced inflammation and thrombolysis may play a critical role in worsening the disease. Hyper activation of the TCA cycle is evident and a macrophage enriched enzyme CLYBL is up regulated in COVID-19 patients. As CLYBL converts the immune modulatory TCA cycle metabolite itaconate through the citramalyl-CoA intermediate to acetyl-CoA, an increase in CLYBL may lead to the depletion of itaconate, limiting its anti-inflammatory function. These observations suggest that supplementation of itaconate and inhibition of CLYBL are possible therapeutic options for treating COVID-19, opening an avenue of modulating host defense as a means of combating SARS-CoV-2 viruses. Supporting Information The supporting information is available online at 10.1007/s11427-021-2070-y. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.
While precision medicine driven by genome sequencing has revolutionized cancer care, such as lung cancer, its impact on gastric cancer (GC) has been minimal. GC patients are routinely treated with chemotherapy, but only a fraction of them receive the clinical benefit. There is an urgent need to develop biomarkers or algorithms to select chemo-sensitive patients or apply targeted therapy. Here, we carried out retrospective analyses of 1,020 formalin-fixed, paraffin-embedded GC surgical resection samples from 5 hospitals and developed a mass spectrometry-based workflow for proteomic subtyping of GC. We identified two proteomic subtypes: the chemo-sensitive group (CSG) and the chemo-insensitive group (CIG) in the discovery set. The 5-year overall survival of CSG was significantly improved in patients who had received adjuvant chemotherapy after surgery compared with those who received surgery only (64.2% vs. 49.6%; Cox P-value=0.002), whereas no such improvement was observed in CIG (50.0% vs. 58.6%; Cox P-value=0.495). We validated these results in an independent validation set. Further, differential proteome analysis uncovered 9 FDA-approved drugs that may be applicable for targeted therapy of GC. A prospective study is warranted to test these findings for future GC patient care.
Diffuse-type gastric cancer (DGC) and intestinal-type gastric cancer (IGC) are the major histological types of gastric cancer (GC). The molecular mechanism underlying DGC and IGC differences are poorly understood. In this research, we carry out multilevel proteomic analyses, including proteome, phospho-proteome, and transcription factor (TF) activity profiles, of 196 cases covering DGC and IGC in Chinese patients. Integrative proteogenomic analysis reveals ARIDIA mutation associated with opposite prognostic effects between DGC and IGC, via diverse influences on their corresponding proteomes. Systematical comparison and consensus clustering analysis identify three subtypes of DGC and IGC, respectively, based on distinct patterns of the cell cycle, extracellular matrix organization, and immune response-related proteins expression. TF activity-based subtypes demonstrate that the disease progressions of DGC and IGC were regulated by SWI/SNF and NFKB complexes. Furthermore, inferred immune cell infiltration and immune clustering show Th1/Th2 ratio is an indicator for immunotherapeutic effectiveness, which is validated in an independent GC anti-PD1 therapeutic patient group. Our multilevel proteomic analyses enable a more comprehensive understanding of GC and can further advance the precision medicine.
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